Esempio n. 1
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    def test_one_chrom(self):
        logging.info("test_one_chrom")

        output_file = self.file_name("one_chrom")

        storage = LocalCache("local_cache/one_chrom")
        test_storage = storage.join('test_snps')
        test_storage.rmtree('')
        test_snps3 = self.bed[:, self.bed.pos[:, 0] ==
                              3]  # Test only on chromosome 3
        test_snps3_dist = DistributedBed.write(test_storage,
                                               test_snps3,
                                               piece_per_chrom_count=2)

        for test_snps, ref, clear_cache, name in (
            (test_snps3, "old_one", True, "Run with just chrom3"),
            (test_snps3_dist, "old_one", True,
             "Run with distributed test SNPs"),
            (test_snps3, "old_one", False, "Run with just chrom3 (use cache)"),
            (test_snps3_dist, "old_one", False,
             "Run with distributed test SNPs (use cache)"),
        ):
            logging.info("=========== " + name + " ===========")
            results_df = single_snp_scale(
                test_snps=test_snps,
                pheno=self.phen_fn,
                covar=self.cov_fn,
                K0=self.bed,
                cache=self._cache_dict(storage, clear_cache=clear_cache),
                output_file_name=output_file,
            )
            self.compare_files(results_df, ref)
Esempio n. 2
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    def test_local_distribute(self):
        logging.info("test_local_distribute")
        force_python_only = False

        output_file = self.file_name("local_distribute")

        storage = LocalCache("local_cache/local_distribute")
        test_storage = storage.join('test_snps')
        test_storage.rmtree('')
        test_snps = DistributedBed.write(test_storage,
                                         self.bed,
                                         piece_per_chrom_count=2)

        results_df = single_snp_scale(test_snps=test_snps,
                                      pheno=self.phen_fn,
                                      covar=self.cov_fn,
                                      G0=self.bed,
                                      cache=self._cache_dict(storage,
                                                             clear_cache=True),
                                      output_file_name=output_file,
                                      force_python_only=force_python_only)

        self.compare_files(results_df, "old")

        results_df = single_snp_scale(test_snps=self.bed,
                                      pheno=self.phen_fn,
                                      covar=self.cov_fn,
                                      G0=self.bed,
                                      cache=self._cache_dict(
                                          storage, clear_cache=False),
                                      output_file_name=output_file)
        self.compare_files(results_df, "old")
Esempio n. 3
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    def scan_local(local_directory, url=None, logging_level=logging.WARNING):
        '''
        Bootstrap a Hashdown by recursively walking a local directory and finding the local MD5 hashes.
        (A local hash might be wrong if the files are out of date or have OS-dependent line endings.)
        Typically, you'll then want to save the result to a JSON file and then edit that JSON file
        manually to remove uninteresting files.

        :param local_directory: Local directory to recursively walk
        :type path: string

        :param url:  URL to give to the Hashdown. (It will not be checked.)
        :type path: string

        :param logging_level: Logging level for printing progress of the walk. Default
               is logging.WARNING)

        :rtype: :class:`.Hashdown`

        '''
        from pysnptools.util.filecache import LocalCache

        file_to_hash = {}
        localcache = LocalCache(local_directory)
        with log_in_place("scanning", logging_level) as updater:
            for file in localcache.walk():
                updater(file)
                with localcache.open_read(file) as full_file:
                    hash = Hashdown._get_hash(full_file)
                    file_to_hash[file] = hash
        return Hashdown(url, file_to_hash=file_to_hash)
Esempio n. 4
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    def test_low(self):
        logging.info("test_low")

        output_file = self.file_name("low")

        storage = LocalCache("local_cache/low")
        for clear_cache in (True, False):
            if clear_cache:
                storage.rmtree()
            results_df = single_snp_scale(test_snps=self.bed,
                                          pheno=self.phen_fn,
                                          covar=self.cov_fn,
                                          cache=storage,
                                          output_file_name=output_file)
            self.compare_files(results_df, "old")
Esempio n. 5
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 def _fixup(cache_value,default_subfolder='filecache'):
     if isinstance(cache_value,FileCache):
         return cache_value
     if cache_value is None:
         dirpath = tempfile.mkdtemp()+'/'+default_subfolder
         return FileCache._fixup(dirpath)
     if isinstance(cache_value,str):
         from pysnptools.util.filecache import LocalCache
         return LocalCache(cache_value)
     raise Exception("Do not know how to make a FileCache from '{0}'".format(cache_value))
Esempio n. 6
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    def test_one_fast(self):
        logging.info("test_one_fast")

        output_file = self.file_name("one_fast")

        storage = LocalCache("local_cache")
        test_storage = storage.join('one_fast')
        test_storage.rmtree()
        test_snps3 = self.bed[:, self.bed.pos[:, 0] ==
                              3]  # Test only on chromosome 3
        test_snps3_dist = DistributedBed.write(test_storage,
                                               test_snps3,
                                               piece_per_chrom_count=2)

        results_df = single_snp_scale(test_snps=test_snps3_dist,
                                      pheno=self.phen_fn,
                                      covar=self.cov_fn,
                                      G0=self.bed,
                                      output_file_name=output_file)
        self.compare_files(results_df, "old_one")
Esempio n. 7
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 def __init__(self, common_directory, id_and_path_function, leave_space=0):
     from pysnptools.util.filecache import LocalCache
     super(PeerToPeer, self).__init__()
     shared_directory_str = str(common_directory)
     if isinstance(common_directory, str):
         common_directory = LocalCache(common_directory)
     self.common_directory = common_directory
     self.id_and_path_function = id_and_path_function
     self.leave_space = leave_space
     assert not self.common_directory._simple_file_exists(
         "main.txt"
     ), "A common_directory cannot exist where a file already exists."
     self._str = "{0}('{1}',id_and_path_function=...{2}')".format(
         self.__class__.__name__, shared_directory_str, '' if
         self.leave_space == 0 else ',leave_space={0}'.format(leave_space))
Esempio n. 8
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 def storage_closure():
     return LocalCache(temp_dir)